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Machine learning applications for carbon emission estimation
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DOI：10.1016/j.rcradv.2025.200263.png)
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Abstract
En 中文
• Systematic review of ML techniques for estimating carbon emissions across sectors. • Identifies untapped potential in energy and industrial sectors for ML-based emission estimation. • Evaluates ML algorithms' effectiveness, strengths, and limitations in diverse contexts. • Proposes hybrid modeling techniques and optimization algorithms to enhance ML performance. • Recommends sector-specific applications and improved data collection practices for accuracy.
Keywords:
Machine learning
Carbon emission
Systematic literature review
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